Uber veteran Uday Kiramendisethi traces the company’s internal developer stack from homegrown systems such as Michelangelo and Cadence to AI gateways, guardrails and agent-ready cloud workspaces. The conversation examines how faster builds, shared tools and global operational complexity shape engineering productivity at scale.

A sweeping survey of the AI race weighs mounting warnings of catastrophic breaches against the commercial and geopolitical pressures driving labs to accelerate. As models make startling advances in mathematics, software and research, the conversation asks whether alignment, monitoring and security can keep pace with capability.

Salary negotiator Colin Larnell argues that the biggest gains come before a counteroffer, when candidates build internal advocates, test a role’s real scope and turn competing opportunities into leverage. The conversation maps the subtle psychology, company-specific rules and career risks behind high-stakes tech offers.

Meta design director Alex Cornell explains how Muse uses messaging cues, progressive disclosure and personalization to make AI agents feel less like software and more like capable companions. He also shares how the app turns Instagram saves, old blogs and hobby data into shopping guides, memory feeds and highly specific coaching tools.

Peter Kafka and Nilay Patel assess Skydance’s debt-heavy Warner Bros. takeover, with David Ellison betting on consolidation while offering little visible plan for growth. They trace the collision between Hollywood’s legacy franchises and the AI, social media, and streaming platforms eroding their value.

Dave Morin traces a career from Apple’s first Facebook group to Path’s bet on intimate social networks and OpenClaw’s push for personal, open-source AI. He and Matt Van Horn revisit a rejected Google offer, the changing culture of Silicon Valley, and the case for multiplayer agents built around user control.

Meta’s Muse and OpenAI’s Dots are turning AI agents into cute, always-on assistants built to book trips, manage inboxes and take on knowledge work. Their race exposes a thornier question: whether consumers will trade sensitive data and independent recommendations for convenience.

Microservices pioneer Sam Newman argues that distributed systems demand fewer absolutist architectures and more honest choices about failure, customer impact and operational limits. He also weighs production as the ultimate source of truth and warns that AI can erode the shared understanding software teams need.

Persistent AI agents are beginning to sort themselves into two camps: personal assistants that tame the noise of daily life and company agents that accumulate shared institutional knowledge. Every’s team weighs the appeal of a beloved bot against the efficiencies of a single, evolving workplace intelligence.

Casey Newton reports from Berkeley’s Curve conference, where AI leaders are increasingly discussing limits on model intelligence and recursive self-improvement as safety fears sharpen. He also explains why the urgency of AI policy has led him to return to X despite his objections to its ownership and culture.

Tracy Durnell traces her path from a seventh-grade Monet fan site to a personal digital garden, where drafts, links and recurring questions shape an evolving creative practice. She and host James also consider how the indie web can build community without sacrificing the privacy and safety that public posting often lacks.

AI coding agents are remaking software work, pushing engineers toward parallel sessions, Slack-based development and internal agent platforms while the traditional IDE recedes. The shift is accelerating migrations, generating tickets and pull requests, and raising new questions about oversight and cost.

Sen. Adam Schiff argues that voluntary AI safeguards cannot address the technology’s risks to privacy, jobs and national security, calling instead for a powerful federal regulator and clearer rules. The California Democrat also connects tech consolidation, media mergers and concentrated wealth to a broader crisis of public trust.

An OpenAI leader sketches a near future where persistent AI agents handle most online work, while humans trade configuration and rote coding for taste, creativity and collaboration. The conversation considers the strain of agent-driven scale, the need for safety guardrails, and the push to make AI less like an app and more like ambient infrastructure.

Nilay Patel separates AI’s immediate cybersecurity risks from the more speculative fears of sentient machines, arguing that powerful systems need transparent rules before they gain more autonomy. The conversation traces the industry’s calls for regulation to competitive distrust, public unease and a Congress ill-equipped to act.

A claimed breakthrough in deciphering a Medici-era cipher becomes a springboard for a sweeping account of frontier AI’s security failures, evasive behavior and accelerating scientific prowess. The conversation weighs the race to automate AI research against the increasingly thin margin for understanding or containing the systems being built.

A proposed 40,000-acre AI data center in rural Utah became a political disaster after residents learned too late of plans that promised colossal power demands and few local benefits. The fight over Kevin O’Leary’s Wonder Valley exposes how the AI infrastructure rush is colliding with water fears, public process and local democracy.

Sam Altman argues that AI’s real value lies not in replacing people but in giving them more room to create, build and direct their own lives. At OpenAI’s DevDay, he frames autonomous agents, live documents and developer platforms as tools for a new entrepreneurial renaissance.

Cockroach Labs CTO Peter Mattes traces a career through GIMP, Gmail’s storage systems and distributed databases, with B-trees recurring as a durable engineering obsession. He also makes the case that AI coding agents can raise output without sacrificing rigor, provided engineers force them to test, measure and review relentlessly.

A long-running British workplace survey finds that employees have steadily lost discretion over how they do their jobs, even as autonomy remains tied to productivity and wellbeing. Cardiff University’s Alan Felstead argues that managers may be overlooking the expertise closest to the work.